Articles producció científica> Química Analítica i Química Orgànica

Yoghurt standardization using real-time NIR prediction of milk fat and protein content

  • Datos identificativos

    Identificador: imarina:9364441
    Autores:
    Castro-Reigía, D.Ezenarro, J.Azkune, M.Ayesta, I.Ostra, M.Amigo, J.M.García, I.Ortiz, M.C.
    Resumen:
    A system based on near-infrared (NIR) spectroscopy has been developed for the in-line control of the composition of the milk used as raw material for yoghurt production to control the content of protein and fat in the final product, and, therefore, to reduce variability in the production process. Firstly, after selecting the appropriate method for preprocessing NIR data, Partial Least Squares Regression models were built to predict fat and protein content in milk, obtaining good performances. The variance explained of y-block in prediction (R2P) was 0.99 and 0.80, while the Root Mean Square Error of Prediction (RMSEP), was 0.26 and 0.16 for fat and protein, respectively. With those models, it was possible to determine the fat and protein contents in milk in real time, and therefore, the quantity of milk powder and cream added in the manufacturing process of yoghurt could be readjusted. The presented strategy allows the improvement of the homogeneity of the final product, reducing the variability of the nutritional values in more than 70% with respect to the traditional recipe, and also meet the target values according to yoghurt producers for fat and protein content, that is, 10% of fat and 5% of protein.
  • Otros:

    Código de proyecto: Grant agreement No. 824769
    Palabras clave: Yoghurt Protein Proof of concept Partial least squares regression (plsr) Near-infrared (nir) In-line Fat
    Fecha de alta del registro: 2024-11-16
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Journal Of Food Composition And Analysis. 128 106015-
    Referencia de l'ítem segons les normes APA: Castro-Reigía, D.; Ezenarro, J.; Azkune, M.; Ayesta, I.; Ostra, M.; Amigo, J.M.; García, I.; Ortiz, M.C. (2024). Yoghurt standardization using real-time NIR prediction of milk fat and protein content. Journal Of Food Composition And Analysis, 128(), 106015-. DOI: 10.1016/j.jfca.2024.106015
    Tipo de publicación: Journal Publications
    Código de projecto 3: 2021PMF-BS-12
    Autor según el artículo: Castro-Reigía, D.; Ezenarro, J.; Azkune, M.; Ayesta, I.; Ostra, M.; Amigo, J.M.; García, I.; Ortiz, M.C.
    Departamento: Química Analítica i Química Orgànica
    Autor/es de la URV: EZENARRO GARATE, JOKIN
    Resumen: A system based on near-infrared (NIR) spectroscopy has been developed for the in-line control of the composition of the milk used as raw material for yoghurt production to control the content of protein and fat in the final product, and, therefore, to reduce variability in the production process. Firstly, after selecting the appropriate method for preprocessing NIR data, Partial Least Squares Regression models were built to predict fat and protein content in milk, obtaining good performances. The variance explained of y-block in prediction (R2P) was 0.99 and 0.80, while the Root Mean Square Error of Prediction (RMSEP), was 0.26 and 0.16 for fat and protein, respectively. With those models, it was possible to determine the fat and protein contents in milk in real time, and therefore, the quantity of milk powder and cream added in the manufacturing process of yoghurt could be readjusted. The presented strategy allows the improvement of the homogeneity of the final product, reducing the variability of the nutritional values in more than 70% with respect to the traditional recipe, and also meet the target values according to yoghurt producers for fat and protein content, that is, 10% of fat and 5% of protein.
    Acción del programa de financiación 2: Action of the European Union-NextGenerationEU
    Áreas temáticas: Zootecnia / recursos pesqueiros Saúde coletiva Química Nutrição Medicina veterinaria Medicina ii Medicina i Materiais Interdisciplinar Geociências Food science & technology Food science Farmacia Engenharias iii Engenharias ii Engenharias i Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, applied Biotecnología Biodiversidade Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: jokin.ezenarro@urv.cat jokin.ezenarro@urv.cat
    Identificador del autor: 0000-0001-9234-7877 0000-0001-9234-7877
    Acción del programa de financiació 3: Universitat Rovira i Virgili - Banco Santander
    Programa de financiación 2: INVESTIGO programe
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0889157524000498
    Programa de financiación 3: Contratos de personal investigador predoctoral en formación
    DOI del artículo: 10.1016/j.jfca.2024.106015
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2024
    Acción del progama de financiación: Action of the European Union’s Horizon 2020 research and innovation programme
  • Palabras clave:

    Chemistry, Applied,Food Science,Food Science & Technology
    Yoghurt
    Protein
    Proof of concept
    Partial least squares regression (plsr)
    Near-infrared (nir)
    In-line
    Fat
    Zootecnia / recursos pesqueiros
    Saúde coletiva
    Química
    Nutrição
    Medicina veterinaria
    Medicina ii
    Medicina i
    Materiais
    Interdisciplinar
    Geociências
    Food science & technology
    Food science
    Farmacia
    Engenharias iii
    Engenharias ii
    Engenharias i
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Chemistry, applied
    Biotecnología
    Biodiversidade
    Astronomia / física
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